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A channel dynamics model for real‐time flood forecasting
Author(s) -
Hoos Anne B.,
Koussis Antonis D.,
Beale Guy O.
Publication year - 1989
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr025i004p00691
Subject(s) - routing (electronic design automation) , kalman filter , channel (broadcasting) , computer science , flood forecasting , noise (video) , process (computing) , scheme (mathematics) , meteorology , filter (signal processing) , environmental science , flood myth , mathematics , geography , artificial intelligence , telecommunications , computer network , mathematical analysis , archaeology , image (mathematics) , operating system , computer vision
A new channel dynamics scheme (alternative system predictor in real time (ASPIRE)), designed specifically for real‐time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio.